IET Renewable Power Generation (RPG) brings together the topics of renewable energy technology, power generation and systems integration, with techno-economic issues. All renewable energy generation technologies are within the scope of the journal.

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The increasing share of distributed energy resources (DER) in electricity production requires new sources and techniques in grid support services to keep the quality and reliability of power supply high. Addressing this matter, DER systems are required to follow technical grid connection requirements determined by distribution system operators (DSOs). Currently, these requirements widely differ from country to country. Recent studies suggest developing unified grid connection requirements for DER on the international level. This unification currently is the main activity for DSOs and standardisation organisations in the field of grid-connected DER. To support this activity, the present article (i) offers a status report on recent studies relevant to the harmonisation of DER grid connection requirements, and (ii) identifies and discusses current DER grid connection guides, namely standards of international and European standardisation organisations, as well as regulations of national DSOs from Austria, Germany, Ireland, Latvia, Switzerland (German-speaking part) and the United Kingdom. The guides are collected and grouped according to the technical area and technology in a database: http://dergridrequirements.net. The database is a tool for finding relevant DER grid connection guides for a specific region, technical area and/or technology. The target audience of the database is DER system developers.

Recent researches oriented to photovoltaic (PV) systems feature booming interest in current decade. For efficiency improvement, maximum power point tracking (MPPT) of PV array output power is mandatory. Although classical MPPT techniques offer simplified structure and implementation, their performance is degraded when compared with artificial intelligence-based techniques especially during partial shading and rapidly changing environmental conditions. Artificial neural network (ANN) algorithms feature several capabilities such as: (i) off-line training, (ii) nonlinear mapping, (iii) high-speed response, (iv) robust operation, (v) less computational effort and (vi) compact solution for multiple-variable problems. Hence, ANN algorithms have been widely applied as PV MPPT techniques. Among various available ANN-based PV MPPT techniques, very limited references gather those techniques as a survey. Neither classification nor comparisons between those competitors exist. Moreover, no detailed analysis of the system performance under those techniques has been previously discussed. This study presents a detailed survey for ANN based PV MPPT techniques. The authors propose new categorisation for ANN PV MPPT techniques based on controller structure and input variables. In addition, a detailed comparison between those techniques from several points of view, such as ANN structure, experimental verification and transient/steady-state performance is presented. Recent references are taken into consideration for update purpose.

For adaptive hill climbing method, variable stepping is achieved by sizing the change of power over the change of voltage (dPPV/dVPV) and change of power over change of D (dPPV/dD) to appropriate step size using a properly tuned scaling factor. However, the photovoltaic (PV) power versus voltage curve has two different slopes which are the left-hand side of the maximum power point (MPP), and right-hand side of MPP (ROM). The fine-tuned scaling factor for the left-hand side PV slope has good performance at left-hand side of MPP (LOM) but can cause overshoot when system operates at the ROM; while scaling factor properly tuned for the right-hand side PV slope has good performance at ROM but slow voltage response when the system operates at LOM. Dual scaling factor technique is proposed to achieve good performance at LOM and ROM. Besides that, the drawback of implementing hill climbing method on buck converter is discussed, where using constant step size, the hill climbing method has small voltage response at point far from MPP but large voltage response at point near MPP. Based on the results obtained from a lab-scale prototype, it is proven that the proposed method is simple and effective.

This study investigates the feasibility of integrating a single-switch active rectifier layout in an offshore wind farm. The proposed active rectifier topology consists of cascade connection of a diode-rectifier and a DC–DC boost converter. A DC collection grid is considered inside the wind farm, which supplies power to a land grid. Each wind conversion units within the DC collection grid includes a turbine, a generator, and an active rectifier. The DC–DC stage of the active rectifier allows regulating the frequency of generator, controlling the DC voltage to follow the reference signal, mitigating the distortion or ripple in the current signal, and maintaining the fault-ride through capability of the wind farm. The AC output signal from the wind-turbine-generators is converted to DC signal through a non-controlled full-bridge diode rectifier and a controlled DC–DC converter. The dynamic model of the DC–DC boost converter cascaded with the diode-rectifier is derived; and the contribution of pulse width modulation (PWM)-controller to the mitigation of signal variations is evaluated. The results prove consistency of the closed loop PWM-controller, which reduces significantly the gain of disturbances. The results are presented in the form of small-signal transfer functions and simulated using MATLAB software.

This study aims to define an online reactive power control scheme for a wind energy harvesting network such that it regulates the voltage at the transmission level in a manner comparable to a conventional synchronous plant and hence could be integrated in an existing transmission network hierarchical voltage control scheme. For that purpose, all decentralised elements within the network (wind farms and on load tap changing (OLTC) transformers) should be coordinated. In that sense, a central controller needs to be implemented. Unwanted controller interactions may then arise as the various decentralised controllers dynamically respond to the changing set-points received from a central controller. To mitigate these interactions, this study proposes a novel offline optimisation approach for tuning the dynamic settings (i.e. settings that affect the central controller temporal evolution such as time constant, time delays or dead bands). These settings ensure that the centrally determined set-points can actually be achieved in practice, and unlocking such performance is the principle research contribution of the present study.